Brazilian Judiciary Dictionary Engine MCP, Ready to Go
Use the Brazilian Judiciary Dictionary Engine with Claude or Cursor to extract and count Brazilian courts and agencies from legal docs with 100% accuracy.
No credit card required. Experience the power of this integration risk-free.
Extract and count every Brazilian court and regulatory agency from legal documents.
Works with every AI agent you already use
…and any MCP-compatible client
How fast is the Brazilian Judiciary Dictionary Engine MCP Server?
Average time for the server to become ready for requests over the last 14 days, measured until the initialize / tools/list handshake completes. Metrics are updated daily between 00:00 and 04:00 UTC. Create a free account, use this MCP on Vinkius Cloud, and connect it to your AI agent in seconds.
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What AI agents can do with Brazilian Judiciary Dictionary Engine: 1 Tool for Legal Entity Extraction
Use the search_legal_entities tool to find and count every Brazilian court and regulatory agency in your documents.
Search legal entities
Searches your text for known Brazilian legal entities using a strict offline dictionary. This gives you a precise count of every court or agency mentioned.
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Absolute agent control
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Cost control per token
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Managed & monitored infra
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Data protection, DLP by design
Sensitive data is filtered before reaching the model. Access is governed so agents receive only the information they're allowed to use.
Token optimization, real savings
Lower AI costs by delivering the right context instead of unnecessary tools. Better accuracy, faster responses, and fewer wasted tokens.
Brazilian Judiciary Dictionary Engine for Precise Legal Entity Extraction
This is for the legal analyst or paralegal who's tired of manually highlighting every time a court is mentioned in a 500-page PDF. It's for people who need 100% accuracy because a hallucinated court name is a liability, not just a typo.
Legal Researcher
Summarizing jurisdictional reach across multiple cases to identify patterns in litigation.
Compliance Officer
Tracking mentions of regulators like CVM or BACEN in corporate compliance reports.
Data Analyst
Normalizing thousands of documents for a large-scale legal database or research project.
Frequently Asked Questions
Does the Brazilian Judiciary Dictionary Engine find all types of courts? +
Yes, it covers Superior Tribunals, Federal Regional Courts (TRFs), Regional Labor Courts (TRTs), and every State Court (TJs) including TJDFT.
Can I use the Brazilian Judiciary Dictionary Engine for US courts? +
No, this MCP is specifically built for the Brazilian judiciary and regulatory apparatus. For other countries, you'll need to use the custom dictionary parameter.
How accurate is the entity detection? +
It's extremely accurate because it uses strict regex boundary matching against a pre-indexed list. It doesn't rely on AI inference, so it won't hallucinate court names.
Does the Brazilian Judiciary Dictionary Engine include regulatory bodies? +
Yes, it includes major agencies like ANVISA, BACEN, CVM, and CADE, along with others like INPI and ANATEL.
Can I add my own custom agencies to the list? +
You can. The MCP supports an extensible custom JSON dictionary if you need to include entities from other jurisdictions or niche bodies.
Will this help me with labor law cases? +
Yes, it's particularly useful for identifying TRT mentions to help you determine jurisdictional concentration in labor files.
What exactly is pre-indexed? +
The complete Brazilian judiciary: 5 Superior Courts, 6 TRFs, 24 TRTs, 27 TJs (including TJDFT), 3 military TJMs, oversight bodies (CNJ, CNMP, TCU), prosecution and advocacy (AGU, MPF, MPT, MPM, MPDFT, DPU, OAB), and 15 regulatory agencies (CADE, CVM, BACEN, INPI, INSS, SUSEP, ANATEL, ANVISA, ANS, ANAC, ANEEL, ANP, ANA, ANTT, ANTAQ).
Does it cover courts from other countries? +
No. This engine covers exclusively the Brazilian legal system. To add courts from other countries, pass a custom JSON dictionary mapping acronyms to full names. Custom entries are tagged separately in the output.
How are results organized? +
Each detected entity includes its acronym, full official name, category (Superior, TRF, TRT, TJ, TJM, Controle, MP/Advocacia, Regulador), and exact mention count. A category summary is also provided for quick analysis.
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